Erratum to: Modeling kelp forest distribution and biomass along temperate rocky coastlines

Gorman, Daniel; Bajjouk, Touria; Populus, Jacques; Vasquez, Mickaël; Ehrhold, Axel

doi:10.1007/s00227-013-2203-y

Cited by 7 publications

(15 citation statements)

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“…Kain (1971a) suggested that kelp responded differently to high currents and high wave exposures, and the studies of, e.g., Eckman et al (2003) and Bekkby et al (2014) on kelp morphology show that the impact of wave exposure and current speed are different. Our study confirms previous studies on the effects of wave exposure (e.g., Svendsen and Kain, 1971;Sjøtun and Fredriksen, 1995;Sjøtun et al, 1998;Gorman et al, 2012;Pedersen et al, 2012) and increases the relatively scarce knowledge on the effects of current speed and the interaction between these two water flow components (but see Bekkby et al, 2009, FIGURE 3 | The probability of finding dense Laminaria hyperborea kelp forests (canopy kelp abundance class 3) as a function of the interaction between wave exposure and depth (A) and current speed and wave exposure (B). Blue coloring indicates high probability, yellow coloring indicates low probability.…”

Section: Discussionsupporting

confidence: 92%

“…Similar to other studies (Gorman et al, 2012;Smale et al, 2016) we find that high abundance of kelp occurs mainly in moderately exposed and exposed areas, and that kelp abundance decreases down to a single or few kelps per m 2 in very wave sheltered areas. The lack of L. hyperborea kelp in wave sheltered areas is most likely because it is outcompeted by the Saccharina latissima kelp (Kain, 1962).…”

Section: Effects Of Wave Exposure and Ocean Currentsupporting

confidence: 91%

“…Depth was, as expected and found in other studies (Bekkby et al, 2009;Gorman et al, 2012), the most important variable for explaining kelp abundance. Kelp abundance decreases with depth and the deepest observation of dense kelp forests is at 31.8 m depth (single kelps were found at 33.5 m depth), which is comparable to findings in other studies (e.g., Kain and Jones, 1964; lower growth limit of approx.…”

Section: Effects Of Depth and Terrainsupporting

confidence: 91%

“…Water flow may come in the form of wave induced exposure or ocean currents, with wave exposure being more orbital than the unidirectional ocean currents, with a large tidal component (Miller et al, 2011). The effect of wave exposure on L. hyperborea distribution, growth, density, production, biomass, mortality and morphology has been documented in several studies (e.g., Svendsen and Kain, 1971;Sjøtun and Fredriksen, 1995;Sjøtun et al, 1998;Gorman et al, 2012;Pedersen et al, 2012). However, the effect of current speed has been less studied for L. hyperborea (but see Bekkby et al, 2009Bekkby et al, , 2014 and the discussion in Kain, 1971a).…”

Section: Introductionmentioning

confidence: 99%

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The Abundance of Kelp Is Modified by the Combined Impact of Depth, Waves and Currents

et al. 2019

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This study analyses the combined impact of two types of ocean water flow, wave exposure and ocean currents, on kelp Laminaria hyperborea abundance, taking other environmental co-variables into account. The dataset covers many ecoregions along the NE Atlantic (Norwegian) coast, including both the Skagerrak, the North Sea and the Norwegian Sea, from 58 • N to 66 • N. Our results show that the abundance of kelp is modified by the combined impact of depth, waves and currents and that high kelp abundance is found mainly in relatively shallow and flat terrain in wave exposed and low current areas. The analyses reveal significant interactions between wave exposure and both depth and ocean currents, implying depth-specific effects of wave exposure and wave-specific effects of current speed. The somewhat surprising influence of temperature is discussed. The ecological function and ecosystem services of kelp forests are related to kelp abundance. Knowledge on how abundances vary with environmental variables is therefore highly relevant for developing large scale models to quantify and visualize (on maps) macroalgae biomass and ecosystem services, such as wave dampening, carbon storage, and raw material provisioning.

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Section: Discussionsupporting

confidence: 92%

Section: Effects Of Wave Exposure and Ocean Currentsupporting

confidence: 91%

Section: Effects Of Depth and Terrainsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

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The Abundance of Kelp Is Modified by the Combined Impact of Depth, Waves and Currents

et al. 2019

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“…Other Norwegian studies found up to a doubling in biomass in moderately wave exposed compared to more sheltered areas, with a levelling off toward more exposed sites (Andersen, 2007;Pedersen et al, 2012;Norderhaug et al, 2012;van Son et al, 2020). A similar, but somewhat weaker pattern was found for L. hyperborea biomass in north-western France by Gorman et al (2013) and for canopy density in the United Kingdom (Smale et al, 2016).…”

Section: Kelp Characteristics Along Depth and Wave Gradientsmentioning

confidence: 63%

Variation in Population Structure and Standing Stocks of Kelp Along Multiple Environmental Gradients and Implications for Ecosystem Services

et al. 2021

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There is an increasing focus on ecosystem services provided by macroalgae worldwide, many which depend on its structural and morphological characteristics. Here we investigated how characteristics of canopy kelp plants of Laminaria hyperborea varies along the Norwegian part of the NE Atlantic. Ten characteristics related to size, allometry, density, biomass and epiphytes were analyzed along wide gradients of depth, wave exposure and latitude. The analyses were performed on a compiled dataset of 630 scuba samples from different research and monitoring projects along the Norwegian coast (58-71°N). The largest kelps, highest biomass, and highest biomass of epiphytic algae was found in Mid-Norway (63-65°N). While most size-related kelp characteristics were reduced with water depth, they were enlarged with wave exposure. The developed statistical models can be used to calculate site-specific values (and their variation) of the different characteristics at any location based on latitude, depth and wave exposure. These can further be used to map kelp derived ecosystem services. We predicted region-specific estimates of total plant weight, kelp density and kelp biomass. Moreover, the models were applied to estimate living biomass (56 million tonnes fresh weight), carbon standing stock (2.6 million tonnes carbon or 9.5 million tonnes CO2), and carbon sequestration potential (0.46 million tonnes per year) for the Norwegian kelp forests, that were estimated to cover about 5 355 km2. The site- and region-specific estimates are relevant to kelp forest management and for blue carbon accountings.

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Monitoring program design for data‐limited marine biogenic habitats: A structured approach

Loh

Archer

Dunham

2019

Ecology and Evolution

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Marine biogenic habitats—habitats created by living organisms—provide essential ecosystem functions and services, such as physical structuring, nutrient cycling, biodiversity support, and increases in primary, secondary, and tertiary production. With the growing trend toward ecosystem approaches to marine conservation and fisheries management, there is greater emphasis on rigorously designed habitat monitoring programs. However, such programs are challenging to design for data‐limited habitats for which underlying ecosystem processes are poorly understood. To provide guidance in this area, we reviewed approaches to benthic assessments across well‐studied marine biogenic habitats and identified common themes related to indicator selection, sampling methods, and survey design. Biogenic habitat monitoring efforts largely focus on the characteristics, distribution, and ecological function of foundation species, but may target other habitat‐forming organisms, especially when community shifts are observed or expected, as well as proxies of habitat status, such as indicator species. Broad‐scale methods cover large spatial areas and are typically used to examine the spatial configuration of habitats, whereas fine‐scale methods tend to be laborious and thus restricted to small survey areas, but provide high‐resolution data. Recent, emerging methods enhance the capabilities of surveying large areas at high spatial resolution and improve data processing efficiency, bridging the gap between broad‐ and fine‐scale methods. Although sampling design selection may be limited by habitat characteristics and available resources, it is critically important to ensure appropriate matching of ecological, observational, and analytical scales. Drawing on these common themes, we propose a structured, iterative approach to designing monitoring programs for marine biogenic habitats that allows for rigorous data collection to inform management strategies, even when data and resource limitations are present. A practical application of this approach is illustrated using glass sponge reefs—a recently discovered and data‐limited habitat type—as a case study.

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Erratum to: Modeling kelp forest distribution and biomass along temperate rocky coastlines

Cited by 7 publications

References 0 publications

The Abundance of Kelp Is Modified by the Combined Impact of Depth, Waves and Currents

The Abundance of Kelp Is Modified by the Combined Impact of Depth, Waves and Currents

Variation in Population Structure and Standing Stocks of Kelp Along Multiple Environmental Gradients and Implications for Ecosystem Services

Monitoring program design for data‐limited marine biogenic habitats: A structured approach

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